1. Field of the Invention
The invention to which this application relates is to mitigate impulsive noise (IN) in data transmission systems and particularly, although not necessarily exclusively in Orthogonal Frequency Division Multiplexing (OFDM) systems by using an adaptive system based on compressive sensing (CS).
2. Prior Art
Impulsive noise in multi-carrier systems has been a problem in obtaining reliable data communications over both wireline and wireless networks. Many known systems and methods have been proposed to reduce the effects of IN on performances of OFDM based communication systems in wireless, DSL (Digital Subscriber Line) and Power Line Communication (PLC) systems.
One group of known methods use clipping and/or nulling while another group use iterative methods to estimate time or frequency domain IN and then cancel its effects. Another area of research relates to compressive sensing for IN mitigation and in which attempts have been made to reconstruct the time-domain IN from its partial frequency domain measurements. The measurements can be taken at receiver by placing silent subcarriers in an OFDM frame at a data transmitter before Inverse Discrete Fourier Transform (IDFT) and any sparse time-domain signal e(n)—with the number of non-zero samples equals to T—can be reconstructed with high accuracy from its Discrete Fourier Transform (DFT) {tilde over (e)}(k) sampled at only M out of N frequencies (where M<N) provided that M≧TC μ log(N). Here, μ is a coherence parameter and is defined as the maximum inner product between two distinct unit-normed columns of the measurement matrix such as a normalized DFT matrix. In this special case of time-domain IN and frequency-domain measurements, the value of μ is equal to one with the proportionality constant C tightening the bounds and the number of measurements in frequency-domain IN is equivalent to the number zero-subcarriers deployed to reconstruct time-domain IN.
However in the known works on IN mitigation using CS the sparsity of IN is assumed to be constant and thereby the number of pilots to reconstruct IN is also fixed. However, in practical implementations where the data is to be carried in specific data transmission system such as Power Line Communications (PLC) the sparsity of IN changes significantly over time and this in turn limits the application of traditional CS algorithms as in practical systems the sparsity of IN changes considerably over time such that, for example, there are more IN disturbances in some hours of the day than others. Therefore relying on fixed number of zero-subcarriers may not be suitable in all circumstances in that if the disturbance ratio (number of impulses) of the IN is high, the insufficient frequency-domain measurements (zero-subcarriers) will cause inaccurate IN estimation and thus lead to BER degradation. On the other hand, if the disturbance ratio of IN is low but the number of zero-subcarriers is too high or higher than required, it will lead to wastage of available bandwidth and as a result lowered throughput of data.
The aim of the present invention is therefore to develop a Multi Mode Compressive Sensing (MMCS) scheme that adaptively changes the number of pilots used to reconstruct the IN depending on the IN's current severity so as to stabilise the Bit Error Rate (BER) and improve overall system data throughput. A further aim is to provide a system with a variable IN mitigation range in order to allow the concurrent control of the BER and data throughput in a data transmission system.